Congrats Martin! 🥳🥳

Thanks Roland! It’s good to mention here that Hairsplitter is also part of it 😄

Thanks! 😊

Work with @msikic.bsky.social, @rvicedomini.bsky.social, Kresimir Krizanovic
MADRe is open-source, modular, and ready to use.
Check it out:
🔗 github.com/lbcb-sci/MADRe
9/9

A key feature of MADRe is its focus on organisms with sufficient abundance to be assembled.
While low-abundance strains may be underrepresented, this trade-off significantly reduces false-positive identifications, a common issue in strain-level metagenomics.
8/9

We evaluated MADRe on both real and simulated datasets and observed:
✅ Comparable or improved accuracy over existing tools
✅ Clearer and more realistic abundance profiles
✅ Substantial reductions in runtime and memory usage
7/9

While assembly is often considered computationally expensive, we demonstrate that MADRe, by combining assembly with contig-level mapping, is more efficient than directly mapping large volumes of reads to a full reference database. 6/9

To complete the pipeline, MADRe maps reads to the reduced reference database and applies a second round of probabilistic reassignment.
This enhances classification sensitivity and filters false-positive identifications, enabling precise strain-level profiling. 5/9

This reduction identifies candidate genomes present in the sample.
However, this step alone does not eliminate all false positives and does not provide accurate abundance estimates. 4/9